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AI Summary

Lead data architecture and modeling initiatives to support Medicaid, Medicare, and commercial healthcare analytics. Develop strategic data solutions while ensuring regulatory compliance and high performance across complex data environments.

* Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, clients, and other key stakeholders. • Lead data architecture, data modeling, and data movement initiatives to enhance the architecture of data warehouse which supports analytics for Medicaid and Medicare and Commercial healthcare data; including domains such as claims, provider, TPL, and member information subject areas. • Create end-to-end vision on how logical design translates into one or more physical databases, and how the data will flow through the successive stages. • Analyzing and translating business needs into long-term solution data models. • Evaluating existing data systems. Working with the development team to create conceptual data models and data flows. • Ensure that data strategies and architectures are in regulatory compliance. Recognize and identify potential areas where existing policies and procedures require change, or where new ones are needed. • Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality. • Create and maintain data model and metadata policies and procedures for functional design. • Provide technical recommendations and engage with other ETL Architects, Business SMEs and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle and recommend effective solutions to develop high performance and highly scalable data solutions (data marts/warehouse, data mining, and advanced analytics) • Address data-related problems regarding systems integration, compatibility, and multiple-platform integration. • Develop and implement key components as needed to create testing criteria to guarantee the fidelity and performance of data architecture. • Document data architecture and enterprise environment to maintain a current and accurate view of the larger data picture, an environment that supports a single version of the truth and is scalable to support future analytical needs. • Communicate with customer, project team in a timely manner and escalates issues & risks appropriately.


* Strong problem solving, influencing, communication, and presentation skills, self-starter. • Expertise in Data Modeling, Data Strategy and Roadmap for large and complex health entity and systems and implemented large scale end-to-end Data Management & Analytics solutions for more than one large client. • Strong knowledge of regulatory security requirements regarding HIPPA, PHI, PII, and other health care data security standards. • Strong Healthcare domain knowledge of Medicaid, Medicare, and Commercial healthcare data sets. • Expertise with normalized OLTP, OLAP, MDM and Dimensional modeling techniques, Star schemas, slowly changing dimensions, role-playing dimensions, dimensional hierarchies, and data classification. • Expert level SQL skills with direct experience writing complex analytic queries, stored procedures, DDL, DML and DCL. Thorough knowledge of query optimization techniques with the ability to write code to ANSI standards and inspect code written by other developers. • Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival and Data Migration strategies using appropriate tools.


* Experience with Microsoft Azure cloud infrastructure and services (Azure Data Lake Storage, Azure Data Factory, Purview, Azure Maps, etc.) • Experience with Snowflake DBMS • Experience with PowerBI or Tableau

This is a remote position.

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